Triple
T4200403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vatican City flag |
E86050
|
entity |
| Predicate | tiaraSymbolism |
P34702
|
FINISHED |
| Object | papal authority |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: papal authority | Statement: [Vatican City flag, tiaraSymbolism, papal authority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tiaraSymbolism Context triple: [Vatican City flag, tiaraSymbolism, papal authority]
-
A.
tiaraWornByBride
Indicates that a tiara is being worn by a person in the role of a bride.
-
B.
emblemSymbolism
chosen
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
C.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
D.
tailpieceType
Indicates the specific kind or design of tailpiece associated with an instrument or object.
-
E.
clothingSymbolism
Indicates how clothing or attire conveys symbolic meaning, such as status, identity, emotion, or cultural significance, within a given context.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0363bbb8819093f396afe91972e2 |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:49 p.m.